TY - GEN
T1 - Toward Long-Lasting Large-Scale Soft Robots
T2 - 7th IEEE International Conference on Soft Robotics, RoboSoft 2024
AU - Stella, Francesco
AU - Pei, Guanran
AU - Meebed, Omar
AU - Guan, Qinghua
AU - Bing, Zhenshan
AU - Santina, Cosimo Della
AU - Hughes, Josie
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Soft robots promise groundbreaking advancements across various industries. However, soft robots are susceptible to wear, fatigue, and material degradation. Their durability and long-term reliability are often overlooked, despite being critical for the successful deployment of these systems in real-world applications. This article contributes to solving this challenge by identifying metrics that reflect material wear, mechanical hysteresis, and drift occurring during long-term operations in soft architectured materials. While this same pipeline can be generalized to different soft robots, we test these metrics on the trimmed helicoid architectured materials, and we validate the improvement in performance on the Helix soft manipulator. Thanks to the proposed metrics, we demonstrate a 75% reduction in repeatability errors over long-duration experiments.
AB - Soft robots promise groundbreaking advancements across various industries. However, soft robots are susceptible to wear, fatigue, and material degradation. Their durability and long-term reliability are often overlooked, despite being critical for the successful deployment of these systems in real-world applications. This article contributes to solving this challenge by identifying metrics that reflect material wear, mechanical hysteresis, and drift occurring during long-term operations in soft architectured materials. While this same pipeline can be generalized to different soft robots, we test these metrics on the trimmed helicoid architectured materials, and we validate the improvement in performance on the Helix soft manipulator. Thanks to the proposed metrics, we demonstrate a 75% reduction in repeatability errors over long-duration experiments.
UR - http://www.scopus.com/inward/record.url?scp=85193846637&partnerID=8YFLogxK
U2 - 10.1109/RoboSoft60065.2024.10521957
DO - 10.1109/RoboSoft60065.2024.10521957
M3 - Conference contribution
AN - SCOPUS:85193846637
T3 - 2024 IEEE 7th International Conference on Soft Robotics, RoboSoft 2024
SP - 190
EP - 196
BT - 2024 IEEE 7th International Conference on Soft Robotics, RoboSoft 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 April 2024 through 17 April 2024
ER -